Continuous microfluidic flow-through protocol for selective and image-activated electroporation of single cells

Electroporation of cells is a widely-used tool to transport molecules such as proteins or nucleic acids into cells or to extract cellular material. However, bulk methods for electroporation do not offer the possibility to selectively porate subpopulations or single cells in heterogeneous cell samples. To achieve this, either presorting or complex single-cell technologies are required currently. In this work, we present a microfluidic flow protocol for selective electroporation of predefined target cells identified in real-time by high-quality microscopic image analysis of fluorescence and transmitted light. While traveling through the microchannel, the cells are focused by dielectrophoretic forces into the microscopic detection area, where they are classified based on image analysis techniques. Finally, the cells are forwarded to a poration electrode and only the target cells are pulsed. By processing a heterogenically stained cell sample, we were able to selectively porate only target cells (green-fluorescent) while non-target cells (blue-fluorescent) remained unaffected. We achieved highly selective poration with >90% specificity at average poration rates of >50% and throughputs of up to 7200 cells per hour.


Introduction
Electroporation is a widely used tool to transport molecules such as nucleic acids or proteins across the cell membrane, to extract cell components or to eliminate unwanted cells from heterogeneous cell samples. [1][2][3][4] It is used, for example, in cancer therapy to modify specic subtypes of T cells, to generate tumor antigen-presenting dendritic cells or to destroy malignant cells. 5,6 Electroporation-based transfection is also widely used in industry or basic research, either for biomolecule production or for generating transgenic mice. 4,7 Moreover, poration-mediated extraction of cell contents, 8 in combination with omics technologies, can provide insight into any metabolic process in the cell. 9,10 The starting point for most of these applications is heterogeneous cell samples, where only the selected target cells should be treated, while the other cells must remain unaffected.
Standard bulk electroporation offers high efficiency, robustness and exibility in adapting to different cell types, buffers and targets. Alternatively, microuidic approaches have been developed that allow membrane permeabilization on the level of the individual cell. This is achieved by driving the cells through a narrow channel that increases shear force and causes mechanoporation, or using integrated electrodes for electroporation. [11][12][13] However, none of the describe methods provides the ability to permeabilize individually selected target cells from heterogeneous cell samples without presorting (e.g., using FACS). The latter is oen associated with cell damage, cell loss, high investment costs, or is simply not applicable, as is oen the case in the therapeutic context. 14 Alternatives such as micro-and nanoscale technologies offer single-cell precise poration by employing nanopillars, optical tweezers or nano-straws. However, they are very labor-intensive and tedious and do not provide the throughput needed for industrial or medical applications. [15][16][17][18][19] To overcome these limitations, we present a microuidic approach for the selective poration of predened target cells in heterogeneous cell samples based on microscopic observation and real-time image analysis. We employ a commercial camera system to inspect cells owing along a microuidic channel. The cell's characteristics are automatically analyzed to decide whether or not to porate the cell between a pair of electrodes placed downstream.
As a proof of concept, we selectively electroporated cells labeled with a specic uorescence color in a sample of differently stained cells, while leaving the non-target cells unaffected. Independent on the applied pulse voltage, we achieved highly selective cell poration of the target cells with specicities around 90% at throughputs of 7200 cells per hour and sensitivities of at least 50%. Live/dead staining showed that cells were vital 3 days aer treatment. The low complexity and ease of use make our microuidic dieletrophoretic poration approach unique since it only requires an ordinary microscope, a uidic system and a pulse-and signal generator for operation which could be parallelized due to the small footprint of the electroporation unit. Finally, it offers a high degree of exibility regarding the targeted cell type due to its image-based control, and it even allows individual pulse protocols for different target cell types in the same sample.

Microuidic chip and microuidic protocol
A 2D schematic of the top view of the microuidic channel for electroporation is shown in Fig. 1. It has a height and width of 35 mm and 650 mm, respectively and it is made by sandwiching the channel structure made out of photoresist between two glass substrates. The glass substrates are patterned with microelectrodes for dielectrophoretic cell handling (see Methods section). The microuidic system has one sample inlet for cells suspended in poration buffer and one additional buffer inlet to allow the online adjustment of the cell density in the main channel. Besides this, there is a sample outlet anked by two additional inlets of sheath ow. The latter are used for a quick and efficient sampling out of the cells, as the total ow increases from 30 mL h −1 to 1000 mL h −1 .
Cells enter the chip through the cell inlet and are lined up by two deection electrodes (Fig. 1, E 1 and E 2 ). Due to the special electrode conguration in our system (see Fig. 2), the repulsive dielectrophoretic force contains a component both acting in the horizontal and vertical direction, counteracting not only the hydrodynamic force (F hydro ), but also gravitational (F G ) and buoyancy force (F B ). Thus, sedimented cells are lied from the channel bottom towards the channel center 20 while being deected (Fig. 2). This ensures that the cells leave the deection electrodes and enter the cell detection area centered in the focal plane of the microscope.
Image acquisition takes place in a conventional uorescence microscope, where both uorescence signals or transmission images can be used for cell classication (enabling for example cell classication based on uorescent protein expression levels, uorescently-labeled surface markers, or morphological parameters like cell size and shape). In particular, for the present experiments and as a proof of concept, the cells are detected and classied by cytosolic uorescence staining as a model for uorescent protein expression.
Only the cells classied as target (depicted green in Fig. 1) were pulsed between two pulse electrodes (E 3 ) downstream of the detection area for electroporation, while the non-target cells (blue) remained untreated. Due to their small size of only 50 mm × 50 mm, the poration electrodes allow selective and individual poration when cell spacing is 50 mm at minimum. This results in a theoretical maximum processing capacity of approximately ve cells per second at 370 mm s −1 (equals 18,000 cells per hour at 30 mL h −1 ). Finally, aer leaving the poration area, the cells are driven to the outlet and ushed from the chip in a controlled manner using a sheath ow to be collected in a 96well plate.

Synchronization of cell movement and pulse application with optical LED feedback
The decision to pulse a cell is made aer the analysis in the cell detection area directly in front of the pulse electrode ( Fig. 1, E 3 ). Images are acquired at a frame rate of 100 fps, which corresponds to a camera cycle of 10 ms. As schematized in Fig. 3, a custom-made Python script reads the frame, detects and tracks the cells, excluding cell clusters, and analyzes the color for each camera cycle. When a target cell is detected at a certain distance from the poration electrode, a message is sent to the main Labview controller soware via an internal TCP/IP communication. Aerwards, an Arduino also controlled by LabVIEW generates a trigger signal for the pulse generator with  a time delay (Dt) to allow the cell to get exactly between the pulse electrodes before pulse application. The pulse generator generates a predened sinusoidal pulse that is fed into the pulse electrodes.
Since the cell is in motion and is only between the pulse electrodes for the short time period of 80 ms, precise determination of pulse delay aer cell detection is a key challenge. Not only the time required for the cell to move from the detection area to the pulse electrodes must be considered but also the latency in image acquisition, image processing and communication between the devices must be compensated for. This makes it hard to estimate the correct time delay theoretically.
To ensure the synchronization between the poration pulse and the presence of the target cell between the pulse electrodes, an optical feedback system was established. For that, the same signal that triggers the pulse generator was used in parallel to drive an LED that illuminates the region of interest to provide accurate optical feedback on when the pulse occurs (Fig. 3). In this way, the necessary pulse delay can be experimentally adjusted. The position of the cell at the time of LED pulse application can then be observed in the video stream to verify that the pulse delay is applied exactly when the cell is between the pulse electrodes ( Fig. 3A and video in ESI †). This delay is dependent on the ow rate and calculates to 75 ms for 370 mm s −1 . The determination of the delay needs to be done once and kept constant for subsequent experiments with the same ow rate.
With our system, we selectively electroporated target cells from a heterogeneous cell sample (Fig. 4). For that, we ushed a mixture of blue and green uorescently stained cells with a ratio of 1 : 1 through the chip. Green stained cells were dened as target cells, blue stained cells as non-target cells. Propidium iodide (PI) was added to the channel medium, serving as an indicator to measure the cell poration depicted as red dots in Fig. 1. This dye is membrane-impermeable in intact cells but can enter the cytoplasm through a porated cell membrane and start to uoresce in red color upon intercalation in nucleic acids.
There had to be sufficient distance between the lined-up cells to reduce the probability of more than one cell being pulsed at the same time. This was ensured by adjusting the cell concentration such that at the applied ow velocity of 370 mm s −1 , 0.2 to 2 cells per second passed between the pulse electrodes. This corresponds to a mean cell distance of 185-1850 mm (i.e., more than three times larger than the poration electrode diameter). Single sinusoidal electrical pulses with a period length of 100 ms and eld strengths of 5, 7, or 9 kV cm −1 root mean square (RMS) were applied for cell poration. A sheath ow of conditioned cell culture medium was used to ush the cells out of the uidic system and to recollect them in a 96-well plate. The amount of intracellular nucleic acid-bound PI was subsequently quantied semi-quantitatively in both blue and green stained cells with an automated uorescence microscope (see Methods section). Processed samples were compared with non-pulsed controls (i.e., cells from the cell culture ask (control, Fig. 4B) or cells that were driven through the chip but did not experience any pulse (0 V condition, Fig. 4B)).
At a low eld strength of 5 kV cm −1 RMS, the poration rate (i.e., amount of PI-positive cells) of the green cells was 53% and increased to 87% and 95% when using 7 kV cm −1 and 9 kV cm −1 RMS, respectively. In contrast, only a slightly higher amount of porated cells (about 4%) was observed in the blue non-target cells compared to the non-pulsed cells of both colors in the control or 0 V condition.
As Fig. 4C shows, we observed a strong red uorescence shi above the arbitrary threshold of 200 (see Methods section) in most of the target cells for a eld strength of 9 kV cm −1 RMS, while most of the non-target cells or non-pulsed cells (0 kV cm −1 RMS) did not exhibit signicant red uorescence (see Fig. 4C).
The performance of the system is particularly evident when considering the selectivity of the poration process in terms of sensitivity and specicity over all experiments (Table 1).
Sensitivity describes the fraction of porated target cells (i.e., green uorescent, no PI-stain) among all target cells, while specicity describes the fraction of non-porated non-target cells (i.e., blue uorescent, no PI-stain) among all non-target cells.
The sensitivity increases with increasing pulse intensity. Compared to the background control with just 6% of porated Fig. 3 Schematic of the set-up for triggered pulse application and optical feedback mechanism for determining pulse delay. (A) When a green-stained cell enters the cell detection area, a custom Python script that constantly analyzes the camera images identifies the cell as target and activates a LabVIEW script. The latter sends a command to an Arduino board, which in turn sends a trigger signal to a function generator to generate a sine wave pulse for electroporation (see B). Since the cell takes some time to travel from the detection area to the poration electrodes (Dt = t − t 0 ), the LabVIEW script is triggering the pulse signal with a delay, which is dependent not only on velocity of the cell but also on the latency in image acquisition, image processing and communication between hardware and software modules. For quantification of this delay, we developed an optical feedback mechanism that provides optical feedback on the exact time of occurrence of the pulse. For that, the Arduino board not only triggers the function generator but also drives an LED in parallel, which feeds a light flash into the optical path at the time point of electric pulse application. The light flash appears in the camera image and can thus be precisely matched to the position of the cell in the microchannel (see A). Porated target cells are indicated with a dotted perimeter and cargo with red dots. target cells, the sensitivity increases up to 50.6%, 85.3%, and 92.7% for 5, 7 and 9 kV cm 1 RMS, respectively. This indicates that the pulse is applied in all cases but is more likely to lead to poration the stronger it is. The specicity at 0, 5, 7, and 9 kV cm −1 RMS is 95.5%, 89.5%, 92.5% and 89.7%, respectively. Thus, the system remains highly selective for the target cells across all pulse strengths tested as specicity keeps between 90 and 95%. This proves that the pulse is delivered very limited in the area of the pulse electrodes and does not affect other cells.

Vitality rate
It is well-known, that depending on the intensity of electroporation, some of the cells will not survive the process. 3 Therefore, we studied the vitality rate of the cells aer electroporation (Fig. 5). For this purpose, all cells of a population were pulsed with different eld strengths, collected in a 96-well plate and cultured in conditioned cell culture medium for 3 or 4 days. The inuence of ushing in and out, e.g. by shear forces and by the mere deection of the DEP electrodes, is reected by the condition without pulse (0 kV cm −1 ). As a control, a sample directly from the culture ask was diluted to a similar cell density (ca. 2000 mL −1 ) and cultivated. To avoid dye-induced effects on vitality rate, unstained cells were used and pulse application was triggered upon cell detection in the bright eld image. The vitality rate of the cells was determined by staining them with a live-and dead staining assay of CellTrace calcein green AM and PI and determining the ratio of calcein-positive cells (live) and PI-positive cells (dead).
Flushing and dielectrophoretically deecting the cells in the channel had only minor effects on the vitality rate. Compared to the control group the vitality rate was only slightly reduced (92% vs. 99%, respectively). The same was true for cells that were electroporated with a eld strength of 5 kV cm −1 RMS, showing a vitality rate of 89%. Those cells pulsed with 7 kV cm −1 RMS and 9 kV cm −1 RMS, however, showed strongly reduced vitality rates of only 40% and 18%, respectively.

Discussion
In this work, we present for the rst time a microuidic owthrough system for visually-triggered selective electroporation of single target cells in heterogeneous cell samples. Cells were In case of the green (target) cell, the red optical feedback flash in the moment of pulse application appears exactly when the cell is anticipated between the poration electrodes. In contrast, the blue (non-target) cell passes the electrodes without being pulsed. (B) A heterogeneous mixture of green and blue fluorescent cells were flushed through the chip. Target cells were either electroporated with pulses of 100 ms length and various electric field strengths (given in RMS) or did not receive any pulses (i.e., 0 kV cm −1 ). PI in the channel medium entered the cell upon membrane poration and, thus, served as poration indicator. After treatment, cells were recollected from the chip in microplates and the amount of PI-positive cells (i.e., poration rate) was determined in the fluorescence microscope. As a control, a sample from the cell culture bottle was diluted comparably to the samples from the chip and analyzed in the same way. (C) Mean red fluorescence intensities of green-and blue-stained cells before (top) and after (bottom) treatment in the chip as described above (exemplary data at 9 kV cm −1 ). The red line indicates the threshold of 200 below which the fluorescence value of 95% of the non-pulsed cells is and above which a cell is counted as porated. detected in both uorescence and transmitted light images. For pulse application, we used 50 mm small thin lm microelectrodes present at the inner surface of the microchannel in order to apply electric elds very locally in only a small region between the electrodes. This allows the electric eld effects to be applied with pinpoint accuracy to the cell membrane of the target cells without affecting other cells present in the rest of the microchannel. The high selectivity of our approach is clearly demonstrated by the results regarding color-based cell poration shown in Fig. 4 and Table 1.
Here, cells were either pulsed or not at different eld strengths during their passage through the microchannel depending on their uorescence color (green: target cell; blue: non-target cell) and the permeabilization of the cell membrane was visualized via a third uorescence color (red). While the amount of permeabilized cells within the target cells increased with the applied eld strength, the amount of porated nontarget cells (and with that the specicity or erroneous poration) remained constant close to background level (which is present in each sample, including untreated cells). Thus, only the selected target cells that were located between the two porating electrodes at the time point of pulse application were successfully permeabilized but not neighboring cells or even cells in other regions of the microchannel, demonstrating the high selectivity of our electroporation protocol.
In general, a sigmoidal relationship can be assumed between the poration rate and the applied eld strength (see also ref. 21). While in the plateau areas at very low or very high effect strength only small changes in the poration rate with varying eld strength are to be expected, this variability is greatest around the half-maximum value. The scatter bars in Fig. 5 show the variability over different experimental runs performed on different days and with different microuidic chips. Slight differences in channel height, material properties of the porating electrode or other experimental conditions could have resulted in different effective eld strengths at the same applied voltage. This would cause the largest deviations in the halfmaximum range (i.e. around 5 kV cm −1 ), while less pronounced effect variations can be expected at lower or higher voltage regimes.
An intrinsic benet of employing highly localized electric elds in the microuidic environment compared to bulk methods is the high control and low variability of the pulse conditions for each cell of the sample. Local variations in eld distribution do not come into play in our system. Instead, each cell is treated in the same way as it passes through the poration unit, allowing for highly reproducible results. However, we observed that the poration performance of our chips decreased with the number of experiments performed (data not shown), which noticeably reduced the number of experiments per chip. It is possible that electrochemical processes on the electrodes are responsible for the observed effects by gradually eroding them.
Moreover, as with other bulk methods, we see a trade-off between poration rate and cell vitality rate. 19,22,23 Although we observed up to 89% vital cells 3 days aer electroporation (see Fig. 5), we did not observe considerable cell proliferation from any condition during cultivation period of 5 days (data not shown). Hence, future optimization of our poration buffer and pulse shapes will be necessary to improve the performance and overcome the limitations of our current approach.
In these proof-of-concept experiments, cytoplasmic dyes were used to demonstrate the basic feasibility of the approach, and also being a model system for uorescent protein marker expression like GFP or CFP. Of course, other relevant biological questions could be addressed that involve cell classication based on the presence or absence of uorescently labeled surface markers, subcellular uorescence distribution, colocalization of proteins or even morphological characteristics like size and shape of unlabeled cells detected in transmitted light mode. So working with uorescently labeled and nonlabeled cells is possible with our microscope-based approach, depending on the desired application and cell classication criteria.
We have already performed some image analysis when segmenting the cells from the image, discarding cell clusters and tracking the exact position of each single cell to activate the poration pulse. Employing automated image analysis for cell analysis offers enormous exibility with regard to the criteria by which a target cell can be dened without the need of modifying the microuidic ow cell. As mentioned above, it even opens up the possibility to choose between cells considering spatial cues (i.e., high-content features) such as cell shape, subcellular localization of proteins, nuclear/cytoplasmic ratio, and many more. [24][25][26][27][28][29][30][31] Thanks to the dielectrophoretic control, the cells are owing in a well-controlled manner along the microchannel at any ow rate. Therefore, the ow velocity can be adjusted easily to allow the necessary computing time even for complex cell Fig. 5 Cell compatibility of the microfluidic electroporation protocol. Unstained cells were introduced into the microfluidic system and electroporated with pulses of various field strengths. We used the same protocol as described in color-based cell poration, but in contrast we used bright-field microscopy for cell detection and porated all the cells in the buffer without addition of PI. Afterwards, the cells were re-collected from the microfluidic system and further grown in cell culture vessels. The amount of vital cells (i.e., vitality rate) was analyzed after 3 or 4 days by staining the cells with calcein green and PI. As a control, we diluted a sample from the cell culture bottle comparably to the samples from the chip and analyzed it in the same way. Field strengths are given in RMS. Experiments were replicated four times (n = 4), except for 7 and 9 kV cm −1 conditions, which were performed one time each (n = 1). classication algorithms on the expense of throughput. Alternatively, the distance between the cell detection area and the position of the poration electrode could be adjusted when longer computing time between image acquisition and pulse application is needed. This exibility in computational time, even up to hundred milliseconds, gives us the possibility to combine our microuidic approach with more advanced and complex deep learning algorithms. 32,33 When spatial cues are used for identifying target cells, motion blur must be taken into account and minimized, depending on the desired image quality. We have worked here with an illumination time of 4 ms, which corresponds to a movement of 1480 nm at a speed of cells of 370 mm s −1 . At 20× magnication, this corresponds to a traveled distance of about 30 mm on the camera chip during exposure time. With a pixel size of 6.5 mm, this thus generates only moderate motion blur (ca. 5 pixels, while a 12 mm-sized cell spans about 37 pixels), which is sufficient for the application shown. However, depending on the desired spatial cue and throughput, this value can be adjusted very easily by reduction of the ow velocity or shortening exposure times in combination with a stronger light source, a more light-intense objective or the use of brighter uorescent markers.
The present throughput is well above the performance of other selective single-cell poration methods, where only few cells per minute can be processed 34,35 and is sufficient for research applications (e.g. cloning or single-cell sequencing). However, the technically simple combination of DEP electrodes for cell focusing and individually switchable poration electrodes in one system allows easy parallelization by stringing several poration lines side by side within the channel. This could help to increase the throughput of our system, which is currently at 7200 cells per hour with only one poration unit.
One very important advantage of our system is its technologically simplicity. Apart from the microscope and the micro-uidic ow cell, it only requires a normal PC, a simple selfdeveloped signal generator, a commercially available function generator and conventional pressure pumps for its operation, which both makes it easy to implement the system in any lab and paves the way for future device development. Moreover, the chip-based approach even allows for future development as an all-in-one disposable solution, which could be attractive for GMP processes, like adoptive T cell transfer or other therapeutic applications. As the microuidic chip can be easily operated on any type of microscope, our approach can be combined with a wide range of imaging techniques (e.g., epi-uorescence, phase contrast, holography, Raman spectroscopy etc. 36 ) to identify target cells, which makes it an interesting generalpurpose tool in biotechnology and biomedical research.

Conclusions
In this work, we present a microuidic protocol for the visually triggered electroporation of individually selected target cells in heterogeneous cell samples. Cells ow through a microchannel and are guided into the microscopic imaging area by dielectrophoretic forces. There, the target cells are imaged and iden-tied by automated image analysis and, depending on the result of the classication, are pulsed or not pulsed at a poration electrode. Thanks to the image-guided control, the system can be quickly and easily adapted to a large number of different samples and target cell types. In addition, morphological (high-content) features in the cells can be used in the future to identify the target cells. Due to the precisely dened electric eld conditions, it offers a high degree of control and selectivity over the electroporation process and thus generates highly reproducible results.
The system is of low complexity and, in addition to the ow cell, only requires a commercially available microscope, a pulse and signal generator, pumps and a PC for control. All this makes it an interesting tool for biomedical research and bio manufacturing, and, in its future version as a disposable cartridge, might be useful also for medical applications.

Cell culture
Cells of human T cell line Jurkat (ACC 282, DSMZ, Germany) were cultivated at 37°C and in 5% CO 2 atmosphere in RPMI 1640 with phenol red, 25 mM HEPES (Pan Biotech, Germany), 2 mM stable L-glutamine (Pan Biotech, Germany) and supplemented with 10% FCS (Biochrom, Germany). Cells which were already processed in the microuidic chip were cultivated aerwards in conditioned medium prepared as follows: Jurkat cells were cultivated in cell culture medium as described earlier + 100 U mL −1 penicillin/streptomycin (Pan Biotech, Germany) with an initial cell density of 10 5 cells per mL. Aer 3 days, the supernatant was sterile ltered and mixed with fresh medium at a ratio of 2 : 1 and a total concentration of 1 mM sodium pyruvate (Pan Biotech, Germany).

Poration buffer
For dielectrophoretic deection and poration in the micro-uidic chip, we used a self-adapted poration buffer as the channel medium in which the cells were previously washed once (300 g, 2 min). The buffer consisted of 220 mM sorbitol (VWR BDH Chemicals, Germany), 25% PBS (Biowest, Germany) and 0.5% PVA (MW approx. 30 000, cas 9002-89-5, Merck, Germany), which resulted in a conductivity of 0.4 S m −1 and osmolarity of 300 mOsmol L −1 . This formulation emerged from preliminary experiments and allows both electroporation and dielectrophoretic deection of cells.

Fluidic setup
The microuidic chip was fabricated by GeSiM mbH, Germany according to our design. We used pressure driven pumps (LineUp series, Fluigent, Germany) with ow sensors (FlowEZ series, Fluigent, Germany) for cell injection, buffer, and sheath ow. The ow rate inside the main channel was 30 mL h −1 (370 mm s −1 ) and sheath ow had a combined ow rate of 1000 mL h −1 . FEP tubing (OD 1.59 mm ID 0.254 mm, Techlab, Germany), PEEK tubing (OD 0.79 mm ID 0.15 mm, Techlab, Germany) and valves (Diba Omnit, Germany) were used to connect reservoir, chip and pumps. 1.5 mL tubes were used as cell and buffer reservoirs and 15 mL tubes for the sheath ow medium.

Dielectrophoretic cell handling and chip design
The principle of dielectrophoresis (DEP) is only briey outlined here, as the effect has been published in detail before. [37][38][39][40][41][42] Shortly, DEP occurs when a dielectric particle is placed in an inhomogeneous electric (AC or DC) eld. This particle is thus polarized, the strength of polarization depending on the voltage gradient of the electric eld, the eld frequency and the electrical conductivity and permittivity of the particle and the surrounding medium. By interaction of these charges with the electric eld, a force acts on the particle, either directed to the eld maximum (attraction towards electrode, positive DEP) or to the eld minimum (repulsion from the electrode, negative DEP), the latter being used in our set-up.
In the 35 mm high microuidic chip, platinum thin lm electrodes (width 15 mm, thickness 200 nm) are arranged in congruent pairs at the inner sides of top and bottom glass. They are driven by a custom-built multichannel electrical signal generator, which produced individually switchable square wave signals for each electrode with a frequency of 300 kHz and amplitudes of 3-4.5 V pp (i.e., 0.9-1.3 kV cm −1 ). The control commands are sent via USB and are transferred in ca. 2 ms for switching all electrodes. Using poration buffer with a conductivity of 0.4 S m −1 , Jurkat cells experience negative DEP and are repelled from the electrodes. This makes the electrodes act as barriers to the cells, causing them to be deected from their streamline when electrodes are arranged at an angle to the ow direction.

Control soware
A LabVIEW (National Instruments, USA) interface was the core control system and accomplished the interaction of all hardware devices as well as the communication with the image recognition soware written in Python. The signals to trigger the pulse generator as well as the optical feedback LED as pulse indicator were generated using a self-congured Arduino nano board (Arduino, Italy).

Sample preparation
To measure the efficiency of selective poration of target cells, we used a heterogeneous sample of green (calcein AM, Invitrogen, USA, 1 mM) and blue (calcein violet AM, Invitrogen, USA, 5 mm) stained cells at a ratio of 1 : 1. Staining was performed with a cell density of 3 × 10 5 to 10 6 cells per mL at room temperature for 30 min. PI (Acros Organics), a red uorescent cell membrane impermeable intercalating nucleic acid dye, was added to the buffer at a concentration of 25 mg mL −1 as a poration indicator. When the dye enters the cell through the porous membrane, there is a shi in uorescence maximum upon binding to nucleic acids, which can be detected as an increasing signal in the red uorescence channel.

Image acquisition and processing
An inverted uorescence microscope (cellR, Olympus) was used to observe and control the poration process in the microuidic chip. It was equipped with a 20× phase contrast objective (Olympus), a triple band lter set (triple band: DAPI, FITC, TxR AHF F62-001 AHF, Germany) for uorescence imaging and a green illumination (Brightline 531/40, AHF Germany) for transmission microscopy. A CMOS color camera with a pixel size of 6.5 mm (Edge 5.5, PCO, Germany) acquired the microscope images at an exposure time of 4 ms and a frame rate of 100 fps. A custom-written Python program running on a common workstation (Intel Xeon E-2136@3.3 GHz, 32 GB RAM, NVIDIA Quadro P620) processed the images and classied the cells. Fluorescence images were used for the selective cell poration experiments, while unstained cells were analyzed in transmitted light images for the viability assays. There were three main tasks accomplished by the image acquisition and processing soware: (i) frame reading and color adjustment, (ii) frame analysis and (iii) communication with the main core soware controlled in LabVIEW. For the rst task, we used python libraries like CuPy, OpenCV-Python and pco to read the frame from the camera, transform 16 bits to 8 bits frame, and dene the dynamic range of the image and nally debayering. The image analysis consisted of cell segmentation, size exclusion to avoid poration of cell clusters, tracking and selection. For the cell segmentation, we used standard morphological transformation, Gaussian ltering as well as color transformation and color and brightness thresholding from the already mentioned OpenCV-Python package. The detected cells were tracked to know the exact position of each of the cells. We computed the distances using functions from scipy.spatial and NumPy, and kept the data in an ordered dictionary from collections. The selection of a target cell is based on color information, in particular, a cell was dened as a target when the contour of the detected cell had a hue value in HSV color space in the range of 50-70 (representing green in a space from 0 to 180). Finally, if a target cell was detected at a certain distance from the poration electrode, a triggering message was sent to the main control soware in python via a TCP/IP server. The communication was written using the low-level networking interface python package named socket.

Electroporation
A single sinusoidal electrical pulse with a period length of 100 ms was used for porating target cells. In order to achieve the used peak eld strengths of 5 kV cm −1 RMS, 7 kV cm −1 RMS and 9 kV cm −1 RMS, we applied amplitude voltages of 25 V, 35 V and 45 V at an electrode spacing of 35 mm. The pulses were generated with a function generator (33120A, Hewlett Packard, USA) that were amplied vefold (7602M, Krohn-Hite Corporation, USA) to achieve the required voltages.

Post-pulse cell analysis
The recovered cells were measured in an automated inverted uorescence microscope (Olympus IXplore Live with ScanR, 4× objective, Olympus, Hamamatsu digital camera C11440). Fluorochromes were excited at 395/25 nm for blue, 475/28 nm for green and 575/25 nm for red and the emission was measured via multiband lter at 438/29 nm, 555/28 nm and 635/22 nm. First, the blue-and green-stained cells were measured (500 ms and 80 ms) and subsequently the relative intracellular PI amount of the detected cells was determined (red channel, 500 ms). Cells were considered porated, when showing intensity values in the red uorescence channel higher than a threshold of 200. This value was deliberately set very close to a negative control sample, where a majority of more than 95% of the cells would still be considered unporated, so that even a tiny increase in poration rate could be detected.
The vitality rate of the cells was determined by staining them aer 3 days cultivation with a live-and dead staining assay of CellTrace calcein green AM (live staining, 1 mM) and PI (dead staining, 10 mg mL −1 ) for 10 minutes at room temperature and determining the percentage of calcein-positive cells in all cells.
Sensitivity and specicity were calculated with the following formulas:

Conflicts of interest
The authors ensure that there are no conicts to declare.